JuliaAcademy (Prepared by core Julia developers in collaboration with Julia Computing.)
Julia Scientific Programming online course, (Dr. Juan H Klopper, Dr. Henri Laurie)
Exercism Julia Track - Exercises and feedback from a team of welcoming mentors
Jupyter notebooks are available for the following YouTube tutorials over at the JuliaBoxTutorials repository on GitHub.
Intro to Julia (version 1.0) , by Jane Herriman
Intro to Julia for data science, by Huda Nassar
Intro to the Queryverse, a Julia data science stack, by David Anthoff
Intro to dynamical systems in Julia, by George Datseris
Introducción a Julia en español, by Miguel Raz Guzmán
Intro to JuliaDB, a package for working with large persistent data sets, by Josh Day and Shashi Gowda
Intro to solving differential equations in Julia, by Chris Rackauckas
Intro to Julia (version 0.6), by Jane Herriman
The Julia Language's YouTube channel also provides a number of tutorials and various other Julia Language content.
From zero to Julia! by Aurelio Amerio. An expanding series of short tutorials about Julia, starting from the beginner level and going up to deal with the more advanced topics.
Julia Workshop for Physicists by Carsten Bauer (see also JuliaWorkshop19).
A Deep Introduction to Julia for Data Science and Scientific Computing by Chris Rackauckas
The Julia Express (featuring Julia 1.0) by Bogumił Kamiński
Programming in Julia (Quantitative Economics) - by Thomas J. Sargent and John Stachurski. Along with being a complete textbook with Julia code for macroeconomics, this also is a very good introduction to Julia.
A Comprehensive Tutorial to Learn Data Science with Julia from Scratch by Mohd Sanad Zaki Rizvi
Julia language: a concise tutorial by Antonello Lobianco. A basic introduction that includes the main packages.
Zacharias Voulgaris. Julia for Machine Learning. Technics Publications, June 2020.
Tom Kwong. Hands-on Design Patterns and Best Practices with Julia. Packt Publishing, January 2020.
Tanmay Bakshi. Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages. McGraw Hill, November 2019.
Antonello Lobianco. Julia Quick Syntax Reference. Apress, November 2019.
Bogumil Kaminski. Julia プログラミングクックブック. Japanese translation for Julia 1.2 by Hidemoto Nakada. Orairījapan, Tōkyo, October 2019.
Günter Faes. Datenanalyse mit Julia: Einstieg in die Datenanalyse mit der Programmiersprache Julia. Books on Demand, September 2019.
Hayden Klok and Yoni Nazarathy. Statistics with julia: Fundamentals for data science, machine learning and artificial intelligence. September 2019. Draft
Ben Lauwens and Allen B. Downey. Think Julia. O’Reilly Media, June 2019.
Giray Ökten. First Semester in Numerical Analysis with Julia. Florida State University Libraries, April 2019.
Changhyun Kwon. Julia Programming for Operations Research. March 2019.
Mykel J. Kochenderfer and Tim A. Wheeler. Algorithms for Optimization. MIT Press, March 2019.
Paul D. McNicholas and Peter Tait. Data Science with Julia. Chapman and Hall/CRC, January 2019.
Adrian Salceanu. Julia Programming Projects. Packt Publishing, December 2018.
Przemysław Szufel and Bogumił Kamiński. Julia 1.0 Programming Cookbook. Packt Publishing, November 2018.
Ivo Balbaert. Julia 1.0 Programming. Packt Publishing, September 2018.
Julia 1.0 was released on 8 August 2018
Dmitrijs Cudihins. Hands-on Computer Vision with Julia. Packt Publishing, June 2018.
Stephen Boyd and Lieven Vandenberghe. Introduction to Applied Linear Algebra. Cambridge University Press, June 2018.
Anshul Joshi and Rahul Lakhanpal. Learning Julia. Packt Publishing, November 2017.
Dominique Orban and Mario Arioli. DOI Iterative Solution of Symmetric Quasi-definite Linear Systems. Society for Industrial and Applied Mathematics, April 2017.
Tobin A. Driscoll and Richard J. Braun. Fundamentals of Numerical Computation. SIAM-Society for Industrial and Applied Mathematics, 2017.
Jalem Raj Rohit. Julia Cookbook. Packt Publishing, September 2016.
Zacharias Voulgaris. Julia for Data Science. Technics Publications, September 2016.
Avik Sengupta. Julia High Performance. Packt Publishing, April 2016.
Anshul Joshi. Julia for Data Science. Packt Publishing, 2016.
Ivo Balbaert, Avik Sengupta, and Malcolm Sherrington. Julia: High Performance Programming. Packt Publishing, 2016.
Ivo Balbaert. Getting Started with Julia Programming Language. Packt Publishing, 2015.
Malcolm Sherrington. Mastering Julia. Packt Publishing, 2015.
Bruce Tate, Ian Dees, Frederic Daoud, and Jack Moffit. Seven More Languages in Seven Weeks. The Pragmatic Programmers, December 2014.
Julia is ready for the classroom. We encourage instructors to participate in the Julia community resources for questions about Julia or specific packages. This page puts together various resources that instructors may find useful. Tutorials and other learning materials are in the learning section of the website.
Julia Scientific Programming online course, (Dr. Juan H Klopper, Dr. Henri Laurie)
15.053x, Optimization Methods in Business Analytics MOOC (massive online open course), (Prof. James Orlin)
Julia is now being used in several universities and online courses. If you know of other classes using Julia for teaching, please consider updating this list.
AGH University of Science and Technology, Poland
Signal processing in medical diagnostic systems (Tomasz Pieciak), Spring 2015
Arizona State University
MAT 423, Numerical Analysis (Prof. Clemens Heitzinger), Fall 2014
Azad University, Science and Research Branch
CE 3820, Modeling and Evaluation (Dr. Arman Shokrollahi), Fall 2014
Brown University
CSCI 1810, Computational Molecular Biology (Prof. Benjamin J. Raphael), Fall 2014
City University of New York
MTH 229, Calculus Computer Laboratory (Prof. John Verzani), Spring 2014. Also see the MTH 229 Projects page.
Cornell University
CS 5220, Applications of Parallel Computers (Prof. David Bindel), Spring 2014
École Polytechnique Fédérale de Lausanne
[CIVIL 557] Decision-aid methodologies in transportation (Mor Kaspi, Virginie Lurkin), Spring 2017
Emory University
Federal Rural University of Rio de Janeiro (UFRRJ)
TM429, Introduction to Recommender Systems (Prof. Filipe Braida), Fall 2016, Spring 2017
Federal University of Alagoas (Universidade Federal de Alagoas, UFAL)
COMP272, Distributed Systems (Prof. André Lage-Freitas): 2015, 2016, and 2017
Federal University of Paraná (Universidade Federal do Paraná, UFPR)
CM103, Mathematics Laboratory (Prof. Abel Soares Siqueira): 2016, 2017, and 2018
CM106, Nonlinear Optimization (Prof. Abel Soares Siqueira): 2018
Federal University of Uberlândia, Institute of Physics
GFM050, Física Computacional (Prof. Gerson J. Ferreira), Fall 2016
Hadsel High School, Stokmarknes, Nordland, Norway
AnsattOversikt, [REA3034] Programmering og modellering (Programming and modeling with Julia and Snap), 2018 / 19 (High school lecturer Olav A Marschall, M.sc. Computer Science)
IIT Indore
ApplNLA, Modern Applications of Numerical Linear Algebra (Prof. Ivan Slapnicar), June 2016
Iowa State University
STAT 590F, Topics in Statistical Computing: Julia Seminar (Prof. Heike Hofmann), Fall 2014
Massachusetts Institute of Technology (MIT)
6.251 / 15.081, Introduction to Mathematical Programming (Prof. Dimitris J. Bertsimas), Fall 2015
18.06, Linear Algebra: Fall 2015, Dr. Alex Townsend; Fall 2014, Prof. Alexander Postnikov; Fall 2013, Prof. Alan Edelman
18.303, Linear Partial Differential Equations: Analysis and Numerics (Prof. Steven G. Johnson), Fall 2013–2016.
18.337 / 6.338, Numerical Computing with Julia (Prof. Alan Edelman). Fall 2015 (IJulia notebooks). Fall 2013–
18.085 / 0851, Computational Science And Engineering I (Prof. Pedro J. Sáenz)
18.330, Introduction to Numerical Analysis (Dr. Homer Reid), Spring 2013–2015
18.335, Introduction to Numerical Methods (Prof. Steven G. Johnson), Fall 2013, Spring 2015
18.338, Eigenvalues Of Random Matrices (Prof. Alan Edelman), Spring 2015
18.S096, Performance Computing in a High Level Language (Steven G. Johnson, Alan Edelman, David Sanders, Jeff Bezanson), January 2017.
15.093 / 6.255, Optimization Methods (Prof. Dimitris Bertsimas and Dr. Phebe Vayanos), Fall 2014
15.S60, Software Tools for Operations Research (Iain Dunning), Spring 2014
15.083, Integer Programming and Combinatorial Optimization (Prof. Juan Pablo Vielma), Spring 2014
Northeastern University, Fall 2016
MTH3300: Applied Probability & Statistics
Óbuda University, John von Neumann Faculty of Informatics, Institute of Applied Mathematics
[Intelligent Development Tools (Hungarian)]
[Intelligent Development Tools (English)]
[Fundamental Mathematical Methods (English)]
Pennsylvania State University
ASTRO 585, High-Performance Scientific Computing for Astrophysics (Prof. Eric B. Ford), Spring 2014 - github repo
ASTRO 585, High-Performance Scientific Computing for Astrophysics (Prof. Eric B. Ford), Fall 2015 - github repo
Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
Programming in Julia (Prof. Thuener Silva), Summer 2017
Linear Optimization (Prof. Alexandre Street), Spring 2017
Decision and Risk Analysis (Prof. Davi Valladão), Fall 2015
Purdue University
CS51400, Numerical Analysis (Prof. David Gleich), Spring 2016
Royal Military Academy (Brussels)
ES123, Computer Algorithms and Programming Project (Prof. Ben Lauwens), Spring 2018
ES313, Mathematical modelling and Computer Simulation (Prof. Ben Lauwens), Fall 2018
“Sapienza” University of Rome, Italy
Operations Research (Giampaolo Liuzzi), Spring 2015
Optimization for Complex Systems (Giampaolo Liuzzi), Spring 2016
Sciences Po Paris, Department of Economics, Spring 2016.
SGH Warsaw School of Economics, Poland
223490-0286, Statistical Learning Methods (Bogumił Kamiński): Fall 2017, Spring 2018, Fall 2018
234900-0286, Agent-Based Modeling (Bogumił Kamiński): Fall 2017, Spring 2018, Fall 2018
239420-0553, Introduction to Deep Learning module (Bogumił Kamiński): Spring 2018
Southcentral Kentucky Community and Technical College
CIT 120 Computational Thinking (Inst. Bryan Knowles), Online, Fall 2017
Stanford University
AA222, Introduction to Multidisciplinary Design Optimization (Prof. Mykel J. Kochenderfer), Spring 2014
AA228/CS238, Decision Making under Uncertainty (Prof. Mykel J. Kochenderfer), Fall 2014
EE103, Introduction to Matrix Methods (Prof. Stephen Boyd), Fall 2014, Fall 2015
CME 257, Advanced Topics in Scientific Computing with Julia (Mr. Brad Nelson), Fall 2015
EE266, Stochastic Control (Prof. Sanjay Lall), Spring 2016
Tokyo Metropolitan University, Tokyo, Japan
L0407, Exercises in Programming I for Mechanical Systems Engineering (Hiroharu Sugawara): Fall 2018, Fall 2019
TU Dortmund / SFB 823, Germany
One week introductory course into Julia with applications in statistics and economics (Tileman Conring): Spring 2018
Universidad Nacional Autónoma de México
Física computacional (Prof. David P. Sanders), Fall 2014
Métodos numéricos para sistemas dinámicos (Prof. Luis Benet), Fall 2014
Métodos numéricos avanzados (Prof. David P. Sanders and Prof. Luis Benet), Spring 2015
Métodos computacionales para la física estadística (Prof. David P. Sanders), Spring 2015
Universidad Nacional Pedro Ruiz Gallo, Lambayeque, Perú
Julia: el lenguaje del futuro, Semana de Integración de Ingeniería Electrónica, (Oscar William Neciosup Vera), Spring 2015
Universidad Veracruzana, México
Algoritmos Evolutivos y de Inteligencia Colectiva (Jesús A. Mejía-de-Dios), Fall 2019
University at Buffalo
IE 572 Linear Programming (Prof. Changhyun Kwon), Fall 2014
University of Antwerp, Faculty of Pharmaceutical, Biomedical, Veterinary Sciences, October 2016
Computational Neuroscience (2070FBDBMW), Master of Biomedical Sciences, of Biochemistry, of Physics (Michele Giugliano)
University of California, Los Angeles (UCLA)
Stat M230/Biomath 280/Biostat M280, Statistical Computing, Spring 2017 (Prof. Hua Zhou)
University of Cologne, Institute for Theoretical Physics
Computational Physics (Prof. Simon Trebst), Summer 2016
Computational Physics (Prof. Ralf Bulla), Summer 2017
Statistical Physics (Prof. Simon Trebst), Winter 2017
Computational Many-Body Physics (Prof. Simon Trebst), Summer 2018
Advanced Julia Workshop (MSc. Carsten Bauer), Fall 2018
Computational Physics (Prof. Simon Trebst), Summer 2019
Advanced Julia Workshop (MSc. Carsten Bauer), Fall 2019
University of Connecticut, Storrs
CHEG 5395, Metaheuristic and Heuristic Methods in Chemical Engineering (Prof. Ranjan Srivastava), Spring 2018
University of Edinburgh
Spring 2017, MATH11146, Modern optimization methods for big data problems (Prof. Peter Richtarik)
Spring 2016, MATH11146, Modern optimization methods for big data problems (Prof. Peter Richtarik)
University of Glasgow, School of Mathematics and Statistics
An Introduction to Julia, course of Online Master of Science (MSc) in Data Analytics (Theodore Papamarkou), September 2017
University of Oulu
Invited Advanced Julia Workshop (MSc. Carsten Bauer, University of Cologne), Spring 2020
University of South Florida
ESI 6491, Linear Programming and Network Optimization (Prof. Changhyun Kwon), Fall 2015
EIN 6945, Nonlinear Optimization and Game Theory (Prof. Changhyun Kwon), Spring 2016
University of Sydney
MATH3076/3976, Mathematical Computing (Assoc. Prof. Sheehan Olver), Fall 2016
Université Paul Sabatier, Toulouse
Optimization in Machine Learning, (Prof. Peter Richtarik), Fall 2015
MATH0462, Discrete Optimization (Prof. Quentin Louveaux), Fall 2016
MATH0461, Introduction to Numerical Optimization (Prof. Quentin Louveaux), Fall 2016
MATH0462, Discrete Optimization (Prof. Quentin Louveaux), Fall 2015
Université de Montréal
IFT1575, Modèles de recherche opérationnelle (Prof. Bernard Gendron), Fall 2017
IFT3245, Simulation et modèles (Prof. Fabian Bastin), Fall 2017
IFT3515, Optimisation non linéaire (Prof. Fabian Bastin), Winter 2017-2018
IFT6512, Programmation stochastique (Prof. Fabian Bastin), Winter 2018
University of Washington
AMATH 586, Numerical analysis of time-dependent problems (Prof. Tom Trogdon), Spring 2020
Western University Canada
CS 2101A, Foundations of Programming for High Performance Computing. (Prof. Marc Moreno Maza), Fall 2013